{"id":"W4239988388","doi":"10.1515/iupac.83.0469","title":"Workstation","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Glossary; Context (archaeology); Computer science; Field (mathematics); Process (computing); Multidisciplinary approach; Data science; Component (thermodynamics); Management science; Sociology; Engineering; Linguistics; Biology; Mathematics; Social science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001262902,0.002102167,0.001297714,0.002585516,0.001040867,0.00299571,0.003220615,0.001488533,0.1029184],"category_scores_gemma":[0.005576709,0.0006237366,0.001633043,0.003863793,0.0004125818,0.002480538,0.002346136,0.002187735,0.2337807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001508959,"about_ca_system_score_gemma":0.002087402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01533871,"about_ca_topic_score_gemma":0.03127758,"domain_scores_codex":[0.9980933,0.0002597765,0.0002623571,0.0006830154,0.0004431088,0.0002584268],"domain_scores_gemma":[0.9973922,0.0003387314,0.0002106796,0.001061295,0.0007417857,0.0002552466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001151517,0.00003012742,0.001165382,0.0003825483,0.00002142563,0.00001579143,0.00002642225,0.00021447,0.0001379736,0.0008813764,0.9907311,0.006278214],"study_design_scores_gemma":[0.000122789,0.00001979481,0.002887485,0.0002075493,0.0000169567,0.00007590153,0.00007930726,0.0006066291,0.0005055877,0.001839106,0.9936165,0.00002233215],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003803781,0.00009917253,0.000381511,0.0001104886,0.00006039208,0.00004544513,0.9926737,0.002112403,0.004136481],"genre_scores_gemma":[0.0005232157,0.0000532138,0.0005774615,0.00007810897,0.000007019249,0.00007344449,0.9971387,0.0001465879,0.001402153],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.8970816,"threshold_uncertainty_score":0.3442963,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01983031526997958,"score_gpt":0.4379884966880528,"score_spread":0.4181581814180732,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}